Mamba: Linear-Time Sequence Modeling with Selective State Spaces (Paper Explained) Published 2023-12-24 Download video MP4 360p Recommendations 31:51 MAMBA from Scratch: Neural Nets Better and Faster than Transformers 43:26 xLSTM: Extended Long Short-Term Memory 44:05 Beyond A*: Better Planning with Transformers via Search Dynamics Bootstrapping (Searchformer) 1:02:17 RWKV: Reinventing RNNs for the Transformer Era (Paper Explained) 16:01 Mamba - a replacement for Transformers? 57:19 Efficiently Modeling Long Sequences with Structured State Spaces - Albert Gu | Stanford MLSys #46 56:16 Flow Matching for Generative Modeling (Paper Explained) 36:16 The math behind Attention: Keys, Queries, and Values matrices 22:27 MAMBA and State Space Models explained | SSM explained 40:08 The Most Important Algorithm in Machine Learning 1:06:35 MedAI #41: Efficiently Modeling Long Sequences with Structured State Spaces | Albert Gu 17:38 The moment we stopped understanding AI [AlexNet] 2:06:38 This is why Deep Learning is really weird. 37:01 TransformerFAM: Feedback attention is working memory Similar videos 1:14:29 Mamba and S4 Explained: Architecture, Parallel Scan, Kernel Fusion, Recurrent, Convolution, Math 44:23 Deep dive into how Mamba works - Linear-Time Sequence Modeling with SSMs - Arxiv Dives 14:06 Mamba Might Just Make LLMs 1000x Cheaper... 1:04:28 Structured State Space Models for Deep Sequence Modeling (Albert Gu, CMU) 1:20:59 Mamba sequence model - part 1 More results